Nanopublications LDF server

Matches in Nanopublications for { ?s ?p ?o <http://purl.org/np/RAxoQEFSMjgX8RdtKySC2IHo27UAb773Z797udcTkxc44#assertion>. }

• evaluation-measure type GuidedChoicePlaceholder assertion.
• dataset type UriPlaceholder assertion.
• algorithm type GuidedChoicePlaceholder assertion.
• task type GuidedChoicePlaceholder assertion.
• dataset-label type LiteralPlaceholder assertion.
• st60 type OptionalStatement assertion.
• evaluation type LocalResource assertion.
• run type LocalResource assertion.
• evaluation-value type LiteralPlaceholder assertion.
• assertion type AssertionTemplate assertion.
• type label "is a" assertion.
• label label "has the name" assertion.
• hasInput label "uses as input" assertion.
• realizes label "executes an implementation that implements the algorithm" assertion.
• hasValue label "has the result value" assertion.
• hasOutput label "has as output" assertion.
• Run label "run of a Machine Learning experiment" assertion.
• specifiedBy label "measures" assertion.
• evaluation-measure label "the evaluation measure (e.g. Accuracy)" assertion.
• dataset label "the URL of the used dataset" assertion.
• algorithm label "the used algorithm (e.g. Random Forest)" assertion.
• task label "the task performed (e.g. Spam Detection)" assertion.
• dataset-label label "the name of the dataset" assertion.
• evaluation label "an evaluation" assertion.
• run label "this run" assertion.
• evaluation-value label "value of the evaluation result (e.g. 0.81 if the accuracy is 81%)" assertion.
• assertion label "Publishing the evaluation result of a Machine Learning experiment" assertion.
• STATO_0000416 label "precision - precision or positive predictive value is defined as the proportion of the true positives against all the positive results (both true positives and false positives)" assertion.
• STATO_0000415 label "accuracy - in the context of binary classification, accuracy is defined as the proportion of true results (both true positives and true negatives) to the total number of cases examined (the sum of true positive, true negative, false positive and false negative). It can be understood as a measure of the proximity of measurement results to the true value." assertion.
• st10 object Run assertion.
• st30 object task assertion.
• st20 object algorithm assertion.
• st80 object evaluation-value assertion.
• st50 object dataset-label assertion.
• st40 object dataset assertion.
• st70 object evaluation-measure assertion.
• st60 object evaluation assertion.
• st10 predicate type assertion.
• st30 predicate achieves assertion.
• st20 predicate realizes assertion.
• st80 predicate hasValue assertion.
• st50 predicate label assertion.
• st40 predicate hasInput assertion.
• st70 predicate specifiedBy assertion.
• st60 predicate hasOutput assertion.
• st10 subject run assertion.
• st30 subject run assertion.
• st20 subject run assertion.
• st80 subject evaluation assertion.
• st50 subject dataset assertion.
• st40 subject run assertion.
• st70 subject evaluation assertion.
• st60 subject run assertion.
• assertion description "Such a nanopublication describes the results of a Machine Learning experiment, such as the accuracy achieved by a applying a given ML technique on a given dataset. This template is based on <a href="https://ml-schema.github.io/documentation/ML%20Schema.html">ML Schema</a>." assertion.
• assertion hasStatement st10 assertion.
• assertion hasStatement st30 assertion.
• assertion hasStatement st20 assertion.
• assertion hasStatement st80 assertion.
• assertion hasStatement st50 assertion.
• assertion hasStatement st40 assertion.
• assertion hasStatement st70 assertion.
• assertion hasStatement st60 assertion.
• evaluation-measure possibleValue STATO_0000416 assertion.
• evaluation-measure possibleValue STATO_0000415 assertion.
• evaluation-measure possibleValuesFromApi "https://www.ebi.ac.uk/ols/api/select?ontology=stato&fieldList=iri,label,description&q=" assertion.
• evaluation-measure possibleValuesFromApi "http://purl.org/nanopub/api/find_signed_things?type=http%3A%2F%2Fwww.w3.org%2Fns%2Fmls%23EvaluationMeasure&searchterm=" assertion.
• algorithm possibleValuesFromApi "https://www.wikidata.org/w/api.php?action=wbsearchentities&language=en&format=json&limit=5&search=" assertion.
• algorithm possibleValuesFromApi "https://www.ebi.ac.uk/ols/api/select?fieldList=iri,label,description&q=" assertion.
• algorithm possibleValuesFromApi "http://purl.org/nanopub/api/find_signed_things?type=http%3A%2F%2Fwww.w3.org%2Fns%2Fmls%23Algorithm&searchterm=" assertion.
• task possibleValuesFromApi "https://www.wikidata.org/w/api.php?action=wbsearchentities&language=en&format=json&limit=5&search=" assertion.
• task possibleValuesFromApi "https://www.ebi.ac.uk/ols/api/select?fieldList=iri,label,description&q=" assertion.
• task possibleValuesFromApi "http://purl.org/nanopub/api/find_signed_things?type=http%3A%2F%2Fwww.w3.org%2Fns%2Fmls%23Task&searchterm=" assertion.
• assertion hasTag "Machine Learning" assertion.